where \(\alpha \)  is a tunable parameter that is used to control the expected block size.
With the use of this new expectation formula, we establish novel bounds on the convergence rate of RNM depending on the spectral properties of the over-approximating matrix \(\) . For many instances of the problem, the matrix coincides with the data covariance, and spectral decays of such covariances are well understood [1]}. This allows us to predict the decay-specific behavior of RNM with determinantal sampling and recommend the optimal block size.
